Analysis of Transcranial Magnetic Stimulation Based on the Surface Integral Equation Formulation
Goal: The aim of this paper is to provide a rigorous model and, hence, a more accurate description of the transcranial magnetic stimulation (TMS) induced fields and currents, respectively, by taking into account the inductive and capacitive effects, as well as the propagation effects, often being ne...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Cvetkovic, Mario [verfasserIn] |
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| Format: |
Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2015 |
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| Systematik: |
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| Übergeordnetes Werk: |
Enthalten in: IEEE transactions on biomedical engineering - New York, NY : IEEE, 1964, 62(2015), 6, Seite 1535-1545 |
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| Übergeordnetes Werk: |
volume:62 ; year:2015 ; number:6 ; pages:1535-1545 |
| Links: |
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| DOI / URN: |
10.1109/TBME.2015.2393557 |
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OLC1964909716 |
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| 520 | |a Goal: The aim of this paper is to provide a rigorous model and, hence, a more accurate description of the transcranial magnetic stimulation (TMS) induced fields and currents, respectively, by taking into account the inductive and capacitive effects, as well as the propagation effects, often being neglected when using quasi-static approximation. Methods: The formulation is based on the surface integral equation (SIE) approach. The model of a lossy homogeneous brain has been derived from the equivalence theorem and using the appropriate boundary conditions for the electric field. The numerical solution of the SIE has been carried out using the method of moments. Results: Numerical results for the induced electric field, electric current density, and the magnetic flux density distribution inside the human brain, presented for three typical TMS coils, are in a good agreement with some previous analysis as well as to the results obtained by analytical approach. Conclusion: The future work should be related to the development of a more detailed geometrical model of the human brain that will take into account complex cortical columnar structures, as well as some additional brain tissues. Significance: To the best of authors knowledge, similar approach in modeling TMS has not been previously reported, albeit integral equation methods are seeing a revival in computational electromagnetics community. | ||
| 650 | 4 | |a electromagnetic model | |
| 650 | 4 | |a transcranial magnetic stimulation analysis | |
| 650 | 4 | |a brain tissues | |
| 650 | 4 | |a method of moments | |
| 650 | 4 | |a Transcranial magnetic stimulation (TMS) | |
| 650 | 4 | |a brain models | |
| 650 | 4 | |a TMS coils | |
| 650 | 4 | |a Boundary conditions | |
| 650 | 4 | |a bioelectric potentials | |
| 650 | 4 | |a capacitive effects | |
| 650 | 4 | |a transcranial magnetic stimulation induced fields | |
| 650 | 4 | |a electric current density | |
| 650 | 4 | |a quasistatic approximation | |
| 650 | 4 | |a Approximation methods | |
| 650 | 4 | |a geometrical model | |
| 650 | 4 | |a induced electric field | |
| 650 | 4 | |a lossy homogeneous brain | |
| 650 | 4 | |a appropriate boundary conditions | |
| 650 | 4 | |a Brain modeling | |
| 650 | 4 | |a transcranial magnetic stimulation induced currents | |
| 650 | 4 | |a magnetic flux density distribution | |
| 650 | 4 | |a Coils | |
| 650 | 4 | |a patient diagnosis | |
| 650 | 4 | |a equivalence theorem | |
| 650 | 4 | |a human brain | |
| 650 | 4 | |a Surface integral equation approach | |
| 650 | 4 | |a inductive effects | |
| 650 | 4 | |a Vectors | |
| 650 | 4 | |a Mathematical model | |
| 650 | 4 | |a propagation effects | |
| 650 | 4 | |a computational electromagnetics | |
| 650 | 4 | |a transcranial magnetic stimulation | |
| 650 | 4 | |a SIE | |
| 650 | 4 | |a medical computing | |
| 650 | 4 | |a rigorous model | |
| 650 | 4 | |a complex cortical columnar structures | |
| 650 | 4 | |a integral equations | |
| 650 | 4 | |a current density | |
| 650 | 4 | |a surface integral equation formulation | |
| 650 | 4 | |a computational electromagnetics community | |
| 650 | 4 | |a biological tissues | |
| 650 | 4 | |a Integral equations | |
| 650 | 4 | |a Brain | |
| 650 | 4 | |a Electric fields | |
| 650 | 4 | |a Computer-generated environments | |
| 650 | 4 | |a Computer simulation | |
| 650 | 4 | |a Magnetic brain stimulation | |
| 650 | 4 | |a Analysis | |
| 650 | 4 | |a Usage | |
| 700 | 1 | |a Poljak, Dragan |4 oth | |
| 700 | 1 | |a Haueisen, Jens |4 oth | |
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10.1109/TBME.2015.2393557 doi PQ20160617 (DE-627)OLC1964909716 (DE-599)GBVOLC1964909716 (PRQ)c2579-7419d56d8ee43d5fb4be30abd6fb7cf20678c6fbc2fa76a7f1c2f0cadac7ff2f0 (KEY)0037705820150000062000601535analysisoftranscranialmagneticstimulationbasedonth DE-627 ger DE-627 rakwb eng 620 610 DNB XA 48665 AVZ rvk 44.09 bkl 44.40 bkl Cvetkovic, Mario verfasserin aut Analysis of Transcranial Magnetic Stimulation Based on the Surface Integral Equation Formulation 2015 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier Goal: The aim of this paper is to provide a rigorous model and, hence, a more accurate description of the transcranial magnetic stimulation (TMS) induced fields and currents, respectively, by taking into account the inductive and capacitive effects, as well as the propagation effects, often being neglected when using quasi-static approximation. Methods: The formulation is based on the surface integral equation (SIE) approach. The model of a lossy homogeneous brain has been derived from the equivalence theorem and using the appropriate boundary conditions for the electric field. The numerical solution of the SIE has been carried out using the method of moments. Results: Numerical results for the induced electric field, electric current density, and the magnetic flux density distribution inside the human brain, presented for three typical TMS coils, are in a good agreement with some previous analysis as well as to the results obtained by analytical approach. Conclusion: The future work should be related to the development of a more detailed geometrical model of the human brain that will take into account complex cortical columnar structures, as well as some additional brain tissues. Significance: To the best of authors knowledge, similar approach in modeling TMS has not been previously reported, albeit integral equation methods are seeing a revival in computational electromagnetics community. electromagnetic model transcranial magnetic stimulation analysis brain tissues method of moments Transcranial magnetic stimulation (TMS) brain models TMS coils Boundary conditions bioelectric potentials capacitive effects transcranial magnetic stimulation induced fields electric current density quasistatic approximation Approximation methods geometrical model induced electric field lossy homogeneous brain appropriate boundary conditions Brain modeling transcranial magnetic stimulation induced currents magnetic flux density distribution Coils patient diagnosis equivalence theorem human brain Surface integral equation approach inductive effects Vectors Mathematical model propagation effects computational electromagnetics transcranial magnetic stimulation SIE medical computing rigorous model complex cortical columnar structures integral equations current density surface integral equation formulation computational electromagnetics community biological tissues Integral equations Brain Electric fields Computer-generated environments Computer simulation Magnetic brain stimulation Analysis Usage Poljak, Dragan oth Haueisen, Jens oth Enthalten in IEEE transactions on biomedical engineering New York, NY : IEEE, 1964 62(2015), 6, Seite 1535-1545 (DE-627)129358452 (DE-600)160429-6 (DE-576)01473074X 0018-9294 nnns volume:62 year:2015 number:6 pages:1535-1545 http://dx.doi.org/10.1109/TBME.2015.2393557 Volltext http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=7012103 http://www.ncbi.nlm.nih.gov/pubmed/25608302 http://search.proquest.com/docview/1682597805 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC SSG-OPC-PHA GBV_ILN_70 GBV_ILN_170 GBV_ILN_2061 GBV_ILN_2410 GBV_ILN_4219 XA 48665 44.09 AVZ 44.40 AVZ AR 62 2015 6 1535-1545 |
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10.1109/TBME.2015.2393557 doi PQ20160617 (DE-627)OLC1964909716 (DE-599)GBVOLC1964909716 (PRQ)c2579-7419d56d8ee43d5fb4be30abd6fb7cf20678c6fbc2fa76a7f1c2f0cadac7ff2f0 (KEY)0037705820150000062000601535analysisoftranscranialmagneticstimulationbasedonth DE-627 ger DE-627 rakwb eng 620 610 DNB XA 48665 AVZ rvk 44.09 bkl 44.40 bkl Cvetkovic, Mario verfasserin aut Analysis of Transcranial Magnetic Stimulation Based on the Surface Integral Equation Formulation 2015 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier Goal: The aim of this paper is to provide a rigorous model and, hence, a more accurate description of the transcranial magnetic stimulation (TMS) induced fields and currents, respectively, by taking into account the inductive and capacitive effects, as well as the propagation effects, often being neglected when using quasi-static approximation. Methods: The formulation is based on the surface integral equation (SIE) approach. The model of a lossy homogeneous brain has been derived from the equivalence theorem and using the appropriate boundary conditions for the electric field. The numerical solution of the SIE has been carried out using the method of moments. Results: Numerical results for the induced electric field, electric current density, and the magnetic flux density distribution inside the human brain, presented for three typical TMS coils, are in a good agreement with some previous analysis as well as to the results obtained by analytical approach. Conclusion: The future work should be related to the development of a more detailed geometrical model of the human brain that will take into account complex cortical columnar structures, as well as some additional brain tissues. Significance: To the best of authors knowledge, similar approach in modeling TMS has not been previously reported, albeit integral equation methods are seeing a revival in computational electromagnetics community. electromagnetic model transcranial magnetic stimulation analysis brain tissues method of moments Transcranial magnetic stimulation (TMS) brain models TMS coils Boundary conditions bioelectric potentials capacitive effects transcranial magnetic stimulation induced fields electric current density quasistatic approximation Approximation methods geometrical model induced electric field lossy homogeneous brain appropriate boundary conditions Brain modeling transcranial magnetic stimulation induced currents magnetic flux density distribution Coils patient diagnosis equivalence theorem human brain Surface integral equation approach inductive effects Vectors Mathematical model propagation effects computational electromagnetics transcranial magnetic stimulation SIE medical computing rigorous model complex cortical columnar structures integral equations current density surface integral equation formulation computational electromagnetics community biological tissues Integral equations Brain Electric fields Computer-generated environments Computer simulation Magnetic brain stimulation Analysis Usage Poljak, Dragan oth Haueisen, Jens oth Enthalten in IEEE transactions on biomedical engineering New York, NY : IEEE, 1964 62(2015), 6, Seite 1535-1545 (DE-627)129358452 (DE-600)160429-6 (DE-576)01473074X 0018-9294 nnns volume:62 year:2015 number:6 pages:1535-1545 http://dx.doi.org/10.1109/TBME.2015.2393557 Volltext http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=7012103 http://www.ncbi.nlm.nih.gov/pubmed/25608302 http://search.proquest.com/docview/1682597805 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC SSG-OPC-PHA GBV_ILN_70 GBV_ILN_170 GBV_ILN_2061 GBV_ILN_2410 GBV_ILN_4219 XA 48665 44.09 AVZ 44.40 AVZ AR 62 2015 6 1535-1545 |
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10.1109/TBME.2015.2393557 doi PQ20160617 (DE-627)OLC1964909716 (DE-599)GBVOLC1964909716 (PRQ)c2579-7419d56d8ee43d5fb4be30abd6fb7cf20678c6fbc2fa76a7f1c2f0cadac7ff2f0 (KEY)0037705820150000062000601535analysisoftranscranialmagneticstimulationbasedonth DE-627 ger DE-627 rakwb eng 620 610 DNB XA 48665 AVZ rvk 44.09 bkl 44.40 bkl Cvetkovic, Mario verfasserin aut Analysis of Transcranial Magnetic Stimulation Based on the Surface Integral Equation Formulation 2015 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier Goal: The aim of this paper is to provide a rigorous model and, hence, a more accurate description of the transcranial magnetic stimulation (TMS) induced fields and currents, respectively, by taking into account the inductive and capacitive effects, as well as the propagation effects, often being neglected when using quasi-static approximation. Methods: The formulation is based on the surface integral equation (SIE) approach. The model of a lossy homogeneous brain has been derived from the equivalence theorem and using the appropriate boundary conditions for the electric field. The numerical solution of the SIE has been carried out using the method of moments. Results: Numerical results for the induced electric field, electric current density, and the magnetic flux density distribution inside the human brain, presented for three typical TMS coils, are in a good agreement with some previous analysis as well as to the results obtained by analytical approach. Conclusion: The future work should be related to the development of a more detailed geometrical model of the human brain that will take into account complex cortical columnar structures, as well as some additional brain tissues. Significance: To the best of authors knowledge, similar approach in modeling TMS has not been previously reported, albeit integral equation methods are seeing a revival in computational electromagnetics community. electromagnetic model transcranial magnetic stimulation analysis brain tissues method of moments Transcranial magnetic stimulation (TMS) brain models TMS coils Boundary conditions bioelectric potentials capacitive effects transcranial magnetic stimulation induced fields electric current density quasistatic approximation Approximation methods geometrical model induced electric field lossy homogeneous brain appropriate boundary conditions Brain modeling transcranial magnetic stimulation induced currents magnetic flux density distribution Coils patient diagnosis equivalence theorem human brain Surface integral equation approach inductive effects Vectors Mathematical model propagation effects computational electromagnetics transcranial magnetic stimulation SIE medical computing rigorous model complex cortical columnar structures integral equations current density surface integral equation formulation computational electromagnetics community biological tissues Integral equations Brain Electric fields Computer-generated environments Computer simulation Magnetic brain stimulation Analysis Usage Poljak, Dragan oth Haueisen, Jens oth Enthalten in IEEE transactions on biomedical engineering New York, NY : IEEE, 1964 62(2015), 6, Seite 1535-1545 (DE-627)129358452 (DE-600)160429-6 (DE-576)01473074X 0018-9294 nnns volume:62 year:2015 number:6 pages:1535-1545 http://dx.doi.org/10.1109/TBME.2015.2393557 Volltext http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=7012103 http://www.ncbi.nlm.nih.gov/pubmed/25608302 http://search.proquest.com/docview/1682597805 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC SSG-OPC-PHA GBV_ILN_70 GBV_ILN_170 GBV_ILN_2061 GBV_ILN_2410 GBV_ILN_4219 XA 48665 44.09 AVZ 44.40 AVZ AR 62 2015 6 1535-1545 |
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10.1109/TBME.2015.2393557 doi PQ20160617 (DE-627)OLC1964909716 (DE-599)GBVOLC1964909716 (PRQ)c2579-7419d56d8ee43d5fb4be30abd6fb7cf20678c6fbc2fa76a7f1c2f0cadac7ff2f0 (KEY)0037705820150000062000601535analysisoftranscranialmagneticstimulationbasedonth DE-627 ger DE-627 rakwb eng 620 610 DNB XA 48665 AVZ rvk 44.09 bkl 44.40 bkl Cvetkovic, Mario verfasserin aut Analysis of Transcranial Magnetic Stimulation Based on the Surface Integral Equation Formulation 2015 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier Goal: The aim of this paper is to provide a rigorous model and, hence, a more accurate description of the transcranial magnetic stimulation (TMS) induced fields and currents, respectively, by taking into account the inductive and capacitive effects, as well as the propagation effects, often being neglected when using quasi-static approximation. Methods: The formulation is based on the surface integral equation (SIE) approach. The model of a lossy homogeneous brain has been derived from the equivalence theorem and using the appropriate boundary conditions for the electric field. The numerical solution of the SIE has been carried out using the method of moments. Results: Numerical results for the induced electric field, electric current density, and the magnetic flux density distribution inside the human brain, presented for three typical TMS coils, are in a good agreement with some previous analysis as well as to the results obtained by analytical approach. Conclusion: The future work should be related to the development of a more detailed geometrical model of the human brain that will take into account complex cortical columnar structures, as well as some additional brain tissues. Significance: To the best of authors knowledge, similar approach in modeling TMS has not been previously reported, albeit integral equation methods are seeing a revival in computational electromagnetics community. electromagnetic model transcranial magnetic stimulation analysis brain tissues method of moments Transcranial magnetic stimulation (TMS) brain models TMS coils Boundary conditions bioelectric potentials capacitive effects transcranial magnetic stimulation induced fields electric current density quasistatic approximation Approximation methods geometrical model induced electric field lossy homogeneous brain appropriate boundary conditions Brain modeling transcranial magnetic stimulation induced currents magnetic flux density distribution Coils patient diagnosis equivalence theorem human brain Surface integral equation approach inductive effects Vectors Mathematical model propagation effects computational electromagnetics transcranial magnetic stimulation SIE medical computing rigorous model complex cortical columnar structures integral equations current density surface integral equation formulation computational electromagnetics community biological tissues Integral equations Brain Electric fields Computer-generated environments Computer simulation Magnetic brain stimulation Analysis Usage Poljak, Dragan oth Haueisen, Jens oth Enthalten in IEEE transactions on biomedical engineering New York, NY : IEEE, 1964 62(2015), 6, Seite 1535-1545 (DE-627)129358452 (DE-600)160429-6 (DE-576)01473074X 0018-9294 nnns volume:62 year:2015 number:6 pages:1535-1545 http://dx.doi.org/10.1109/TBME.2015.2393557 Volltext http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=7012103 http://www.ncbi.nlm.nih.gov/pubmed/25608302 http://search.proquest.com/docview/1682597805 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC SSG-OPC-PHA GBV_ILN_70 GBV_ILN_170 GBV_ILN_2061 GBV_ILN_2410 GBV_ILN_4219 XA 48665 44.09 AVZ 44.40 AVZ AR 62 2015 6 1535-1545 |
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10.1109/TBME.2015.2393557 doi PQ20160617 (DE-627)OLC1964909716 (DE-599)GBVOLC1964909716 (PRQ)c2579-7419d56d8ee43d5fb4be30abd6fb7cf20678c6fbc2fa76a7f1c2f0cadac7ff2f0 (KEY)0037705820150000062000601535analysisoftranscranialmagneticstimulationbasedonth DE-627 ger DE-627 rakwb eng 620 610 DNB XA 48665 AVZ rvk 44.09 bkl 44.40 bkl Cvetkovic, Mario verfasserin aut Analysis of Transcranial Magnetic Stimulation Based on the Surface Integral Equation Formulation 2015 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier Goal: The aim of this paper is to provide a rigorous model and, hence, a more accurate description of the transcranial magnetic stimulation (TMS) induced fields and currents, respectively, by taking into account the inductive and capacitive effects, as well as the propagation effects, often being neglected when using quasi-static approximation. Methods: The formulation is based on the surface integral equation (SIE) approach. The model of a lossy homogeneous brain has been derived from the equivalence theorem and using the appropriate boundary conditions for the electric field. The numerical solution of the SIE has been carried out using the method of moments. Results: Numerical results for the induced electric field, electric current density, and the magnetic flux density distribution inside the human brain, presented for three typical TMS coils, are in a good agreement with some previous analysis as well as to the results obtained by analytical approach. Conclusion: The future work should be related to the development of a more detailed geometrical model of the human brain that will take into account complex cortical columnar structures, as well as some additional brain tissues. Significance: To the best of authors knowledge, similar approach in modeling TMS has not been previously reported, albeit integral equation methods are seeing a revival in computational electromagnetics community. electromagnetic model transcranial magnetic stimulation analysis brain tissues method of moments Transcranial magnetic stimulation (TMS) brain models TMS coils Boundary conditions bioelectric potentials capacitive effects transcranial magnetic stimulation induced fields electric current density quasistatic approximation Approximation methods geometrical model induced electric field lossy homogeneous brain appropriate boundary conditions Brain modeling transcranial magnetic stimulation induced currents magnetic flux density distribution Coils patient diagnosis equivalence theorem human brain Surface integral equation approach inductive effects Vectors Mathematical model propagation effects computational electromagnetics transcranial magnetic stimulation SIE medical computing rigorous model complex cortical columnar structures integral equations current density surface integral equation formulation computational electromagnetics community biological tissues Integral equations Brain Electric fields Computer-generated environments Computer simulation Magnetic brain stimulation Analysis Usage Poljak, Dragan oth Haueisen, Jens oth Enthalten in IEEE transactions on biomedical engineering New York, NY : IEEE, 1964 62(2015), 6, Seite 1535-1545 (DE-627)129358452 (DE-600)160429-6 (DE-576)01473074X 0018-9294 nnns volume:62 year:2015 number:6 pages:1535-1545 http://dx.doi.org/10.1109/TBME.2015.2393557 Volltext http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=7012103 http://www.ncbi.nlm.nih.gov/pubmed/25608302 http://search.proquest.com/docview/1682597805 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC SSG-OPC-PHA GBV_ILN_70 GBV_ILN_170 GBV_ILN_2061 GBV_ILN_2410 GBV_ILN_4219 XA 48665 44.09 AVZ 44.40 AVZ AR 62 2015 6 1535-1545 |
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Cvetkovic, Mario |
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Cvetkovic, Mario ddc 620 rvk XA 48665 bkl 44.09 bkl 44.40 misc electromagnetic model misc transcranial magnetic stimulation analysis misc brain tissues misc method of moments misc Transcranial magnetic stimulation (TMS) misc brain models misc TMS coils misc Boundary conditions misc bioelectric potentials misc capacitive effects misc transcranial magnetic stimulation induced fields misc electric current density misc quasistatic approximation misc Approximation methods misc geometrical model misc induced electric field misc lossy homogeneous brain misc appropriate boundary conditions misc Brain modeling misc transcranial magnetic stimulation induced currents misc magnetic flux density distribution misc Coils misc patient diagnosis misc equivalence theorem misc human brain misc Surface integral equation approach misc inductive effects misc Vectors misc Mathematical model misc propagation effects misc computational electromagnetics misc transcranial magnetic stimulation misc SIE misc medical computing misc rigorous model misc complex cortical columnar structures misc integral equations misc current density misc surface integral equation formulation misc computational electromagnetics community misc biological tissues misc Integral equations misc Brain misc Electric fields misc Computer-generated environments misc Computer simulation misc Magnetic brain stimulation misc Analysis misc Usage Analysis of Transcranial Magnetic Stimulation Based on the Surface Integral Equation Formulation |
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620 610 DNB XA 48665 AVZ rvk 44.09 bkl 44.40 bkl Analysis of Transcranial Magnetic Stimulation Based on the Surface Integral Equation Formulation electromagnetic model transcranial magnetic stimulation analysis brain tissues method of moments Transcranial magnetic stimulation (TMS) brain models TMS coils Boundary conditions bioelectric potentials capacitive effects transcranial magnetic stimulation induced fields electric current density quasistatic approximation Approximation methods geometrical model induced electric field lossy homogeneous brain appropriate boundary conditions Brain modeling transcranial magnetic stimulation induced currents magnetic flux density distribution Coils patient diagnosis equivalence theorem human brain Surface integral equation approach inductive effects Vectors Mathematical model propagation effects computational electromagnetics transcranial magnetic stimulation SIE medical computing rigorous model complex cortical columnar structures integral equations current density surface integral equation formulation computational electromagnetics community biological tissues Integral equations Brain Electric fields Computer-generated environments Computer simulation Magnetic brain stimulation Analysis Usage |
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ddc 620 rvk XA 48665 bkl 44.09 bkl 44.40 misc electromagnetic model misc transcranial magnetic stimulation analysis misc brain tissues misc method of moments misc Transcranial magnetic stimulation (TMS) misc brain models misc TMS coils misc Boundary conditions misc bioelectric potentials misc capacitive effects misc transcranial magnetic stimulation induced fields misc electric current density misc quasistatic approximation misc Approximation methods misc geometrical model misc induced electric field misc lossy homogeneous brain misc appropriate boundary conditions misc Brain modeling misc transcranial magnetic stimulation induced currents misc magnetic flux density distribution misc Coils misc patient diagnosis misc equivalence theorem misc human brain misc Surface integral equation approach misc inductive effects misc Vectors misc Mathematical model misc propagation effects misc computational electromagnetics misc transcranial magnetic stimulation misc SIE misc medical computing misc rigorous model misc complex cortical columnar structures misc integral equations misc current density misc surface integral equation formulation misc computational electromagnetics community misc biological tissues misc Integral equations misc Brain misc Electric fields misc Computer-generated environments misc Computer simulation misc Magnetic brain stimulation misc Analysis misc Usage |
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ddc 620 rvk XA 48665 bkl 44.09 bkl 44.40 misc electromagnetic model misc transcranial magnetic stimulation analysis misc brain tissues misc method of moments misc Transcranial magnetic stimulation (TMS) misc brain models misc TMS coils misc Boundary conditions misc bioelectric potentials misc capacitive effects misc transcranial magnetic stimulation induced fields misc electric current density misc quasistatic approximation misc Approximation methods misc geometrical model misc induced electric field misc lossy homogeneous brain misc appropriate boundary conditions misc Brain modeling misc transcranial magnetic stimulation induced currents misc magnetic flux density distribution misc Coils misc patient diagnosis misc equivalence theorem misc human brain misc Surface integral equation approach misc inductive effects misc Vectors misc Mathematical model misc propagation effects misc computational electromagnetics misc transcranial magnetic stimulation misc SIE misc medical computing misc rigorous model misc complex cortical columnar structures misc integral equations misc current density misc surface integral equation formulation misc computational electromagnetics community misc biological tissues misc Integral equations misc Brain misc Electric fields misc Computer-generated environments misc Computer simulation misc Magnetic brain stimulation misc Analysis misc Usage |
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Analysis of Transcranial Magnetic Stimulation Based on the Surface Integral Equation Formulation |
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Goal: The aim of this paper is to provide a rigorous model and, hence, a more accurate description of the transcranial magnetic stimulation (TMS) induced fields and currents, respectively, by taking into account the inductive and capacitive effects, as well as the propagation effects, often being neglected when using quasi-static approximation. Methods: The formulation is based on the surface integral equation (SIE) approach. The model of a lossy homogeneous brain has been derived from the equivalence theorem and using the appropriate boundary conditions for the electric field. The numerical solution of the SIE has been carried out using the method of moments. Results: Numerical results for the induced electric field, electric current density, and the magnetic flux density distribution inside the human brain, presented for three typical TMS coils, are in a good agreement with some previous analysis as well as to the results obtained by analytical approach. Conclusion: The future work should be related to the development of a more detailed geometrical model of the human brain that will take into account complex cortical columnar structures, as well as some additional brain tissues. Significance: To the best of authors knowledge, similar approach in modeling TMS has not been previously reported, albeit integral equation methods are seeing a revival in computational electromagnetics community. |
| abstractGer |
Goal: The aim of this paper is to provide a rigorous model and, hence, a more accurate description of the transcranial magnetic stimulation (TMS) induced fields and currents, respectively, by taking into account the inductive and capacitive effects, as well as the propagation effects, often being neglected when using quasi-static approximation. Methods: The formulation is based on the surface integral equation (SIE) approach. The model of a lossy homogeneous brain has been derived from the equivalence theorem and using the appropriate boundary conditions for the electric field. The numerical solution of the SIE has been carried out using the method of moments. Results: Numerical results for the induced electric field, electric current density, and the magnetic flux density distribution inside the human brain, presented for three typical TMS coils, are in a good agreement with some previous analysis as well as to the results obtained by analytical approach. Conclusion: The future work should be related to the development of a more detailed geometrical model of the human brain that will take into account complex cortical columnar structures, as well as some additional brain tissues. Significance: To the best of authors knowledge, similar approach in modeling TMS has not been previously reported, albeit integral equation methods are seeing a revival in computational electromagnetics community. |
| abstract_unstemmed |
Goal: The aim of this paper is to provide a rigorous model and, hence, a more accurate description of the transcranial magnetic stimulation (TMS) induced fields and currents, respectively, by taking into account the inductive and capacitive effects, as well as the propagation effects, often being neglected when using quasi-static approximation. Methods: The formulation is based on the surface integral equation (SIE) approach. The model of a lossy homogeneous brain has been derived from the equivalence theorem and using the appropriate boundary conditions for the electric field. The numerical solution of the SIE has been carried out using the method of moments. Results: Numerical results for the induced electric field, electric current density, and the magnetic flux density distribution inside the human brain, presented for three typical TMS coils, are in a good agreement with some previous analysis as well as to the results obtained by analytical approach. Conclusion: The future work should be related to the development of a more detailed geometrical model of the human brain that will take into account complex cortical columnar structures, as well as some additional brain tissues. Significance: To the best of authors knowledge, similar approach in modeling TMS has not been previously reported, albeit integral equation methods are seeing a revival in computational electromagnetics community. |
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<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a2200265 4500</leader><controlfield tag="001">OLC1964909716</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20220220115740.0</controlfield><controlfield tag="007">tu</controlfield><controlfield tag="008">160206s2015 xx ||||| 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1109/TBME.2015.2393557</subfield><subfield code="2">doi</subfield></datafield><datafield tag="028" ind1="5" ind2="2"><subfield code="a">PQ20160617</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)OLC1964909716</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)GBVOLC1964909716</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(PRQ)c2579-7419d56d8ee43d5fb4be30abd6fb7cf20678c6fbc2fa76a7f1c2f0cadac7ff2f0</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(KEY)0037705820150000062000601535analysisoftranscranialmagneticstimulationbasedonth</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">620</subfield><subfield code="a">610</subfield><subfield code="q">DNB</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">XA 48665</subfield><subfield code="q">AVZ</subfield><subfield code="2">rvk</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">44.09</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">44.40</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Cvetkovic, Mario</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Analysis of Transcranial Magnetic Stimulation Based on the Surface Integral Equation Formulation</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2015</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">ohne Hilfsmittel zu benutzen</subfield><subfield code="b">n</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Band</subfield><subfield code="b">nc</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Goal: The aim of this paper is to provide a rigorous model and, hence, a more accurate description of the transcranial magnetic stimulation (TMS) induced fields and currents, respectively, by taking into account the inductive and capacitive effects, as well as the propagation effects, often being neglected when using quasi-static approximation. Methods: The formulation is based on the surface integral equation (SIE) approach. The model of a lossy homogeneous brain has been derived from the equivalence theorem and using the appropriate boundary conditions for the electric field. The numerical solution of the SIE has been carried out using the method of moments. Results: Numerical results for the induced electric field, electric current density, and the magnetic flux density distribution inside the human brain, presented for three typical TMS coils, are in a good agreement with some previous analysis as well as to the results obtained by analytical approach. Conclusion: The future work should be related to the development of a more detailed geometrical model of the human brain that will take into account complex cortical columnar structures, as well as some additional brain tissues. 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